<p>Prime editing is a is a very precise and safe method. However, depending on the genomic locus targeted, the editing efficiency can be very low. The cystic fibrosis causing CFTR F508del mutation is, as Mattijs Bulcaen[link] stated in our interview, one of, if not the most obvious application of prime editing, considering the large amount of people affected. The lack of publications addressing CFTR target implied, that the mutation might be particularly hard to edit. At low editing efficiency, successful edits are hard, if not impossible to distinguish from the background noise using conventional methods like sanger sequencing or qPCR. As a basis to effectively test our approach and screen for working pegRNAs, we needed a highly sensitive method of detection with as little noise as possible to optimize our prime editing approach for genomic CFTR targeting.</p>
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@@ -209,7 +209,7 @@ export function Engineering() {
<H3id="transfection-header"text="Optimization of Transfection"></H3>
<H2id="transfection-header"text="Optimization of Transfection"></H2>
<p>
To test prime editors, a reliable model system is required. HEK293 cells are a human derived cell line and widely used in a variety of fields in biology<TabScrollLinktab="tab-transfection"num="1"scrollId="desc-1"/>. Apart from easy handling and comparatively easy transfection, they have, as we found out in our exchange with <aonClick={()=>goToPagesAndOpenTab('mattijsinv','/human-practices')}>Mattijs Bulcaen</a>, one advantage over other models: They are naturally impaired in DNA repair mechanisms and therefore easier to edit. To properly compare editing efficiencies, a high transfection efficiency is of utmost importance. This engineering cycle focuses on our work in simulating prime editing using the PEAR reporter system<TabScrollLinktab="tab-transfection"num="2"scrollId="desc-2"/> and optimizing transfection protocols.
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@@ -326,7 +326,7 @@ export function Engineering() {
<p>Different versions of the original prime editing system have been developed since its initial introduction. Deciding on what system to use for the application in therapeutic human gene editing, especially concerning the correction of F508del, was the goal of this engineering cycle.</p>
<p>
Since we aim to develop a therapy delivered to the human body, we wanted to obtain high editing efficiency while risking as little off-targets as possible and also reducing the size for improved packability.
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@@ -503,7 +503,7 @@ export function Engineering() {
<p>The design path of our lipid nanoparticle (LNP) for mRNA delivery underwent multiple cycles of research and discussion, marked by important decision points and learnings along the way. By ongoing further improvement, we designed our lungs-specific LNP called AirBuddy with improved stability aspects, becoming more precise in the delivery of our therapeutic cargo LNP by LNP.</p>